GTM Engineer

THE ROLE

Growth owns the systems that power our go-to-market motion: our CRM, connected to enrichment, sales engagement, outbound agents, lifecycle, routing, visitor intelligence, and paid, with GTM OS, our internal platform, tying them together. We are hiring a GTM Engineer to run that motion and build the agents and data layer it depends on.

Nash builds the autonomic logistics platform: a system that senses what is happening across a network, decides what to do about it, and adjusts as the results come back, without waiting to be told. Our go-to-market should run the same way. A signal comes in, an agent decides what to do with it, the rep gets the account ready to work, and every outcome writes back so the next decision is better than the last.

Most of the pieces exist. GTM OS is in production, the agents run, and the stack is connected. Your job is to turn them into one reliable engine that produces pipeline, hold it to a production bar, then decide what it does next.

WHAT YOU'LL DO

• Build and run the AI agents that work across our GTM motion: account research, signal qualification, message construction, routing, and reply handling, from design through evaluations, rollout, and the monitoring that keeps them honest.

• Build the infrastructure to run paid and ABM as one system: audiences generated from the CRM, campaigns launched and paused by rules you write, engagement flowing back into the agents, and spend tied to accounts worked and pipeline created.

• Own the account context layer every agent and campaign is grounded in: entity resolution, evidence typing, freshness and provenance, and the segment, industry, region, and product rules that define our market.

• Build on GTM OS, our internal platform, and make what it can do available to sales and marketing inside the tools they already use.

• Be the technical owner of our go-to-market systems, the CRM and everything connected to it, from the data model and routing logic to the integrations and automations that keep the whole stack current and consistent.

• Own sending infrastructure and deliverability: domain strategy, warming, suppression, and sender reputation across every program that sends.

• Hold the production bar: evaluations, observability, permissions, and auditability, so the system reports its own failures before a rep finds them.

• Be measured on what the motion produces: reply and meeting rates, pipeline and revenue, cost per account worked. Agent reliability and data quality are how you get there.

WHAT YOU'LL BRING

• A go-to-market record: outbound, paid, ABM, or lifecycle programs you ran, with the pipeline they produced and the systems you built to run them.

• Software you shipped and kept running: a service, agent, or pipeline in production that other people depended on, with something we can look at.

• Outbound that scales and still reads like a person: sequences triggered by something that just changed for the buyer and tied to what we sell, reply rates to show for them, and the judgment to pull apart a message that is not landing.

• Paid media fluency: you have run budgets and built audiences, and you know which decisions should stay with a person.

• Hands-on experience applying AI to go-to-market systems: agents, LLM-based automation, MCP-style integrations, and the evaluations that tell you whether any of it works.

• Fluency in Python or TypeScript, and daily work with Claude Code, Cursor, or equivalent, with specific opinions about where the tooling fails.

• Integration experience: you have built and debugged integrations through APIs and understand auth, rate limits, sync direction, and failure modes.

• Salesforce as a developer: the data model, the API, and Apex, or the track record to pick it up fast.

• Data fluency: SQL, warehouse concepts, and the habit of tracing a data quality issue from source to destination.

• You can turn a vague request into scoped work and explain the tradeoffs.